OCTAD: an open workspace for virtually screening therapeutics targeting precise cancer patient groups using gene expression features
暂无分享,去创建一个
Benjamin S. Glicksberg | Ke Liu | Jing Xing | Billy Zeng | Patrick A. Newbury | Anita Wen | Caven Chow | Bin Chen | B. Glicksberg | E. Chekalin | Ke Liu | Jing Xing | Bin Chen | Billy Zeng | Anita Wen | Caven Chow
[1] Atul J Butte,et al. Computational Discovery of Niclosamide Ethanolamine, a Repurposed Drug Candidate That Reduces Growth of Hepatocellular Carcinoma Cells In Vitro and in Mice by Inhibiting Cell Division Cycle 37 Signaling. , 2017, Gastroenterology.
[2] A. Butte,et al. Leveraging big data to transform target selection and drug discovery , 2016, Clinical pharmacology and therapeutics.
[3] A. Jemal,et al. Global Cancer Statistics , 2011 .
[4] Rong Chen,et al. Systematic analyses of drugs and disease indications in RepurposeDB reveal pharmacological, biological and epidemiological factors influencing drug repositioning , 2017, Briefings Bioinform..
[5] Mary Goldman,et al. Toil enables reproducible, open source, big biomedical data analyses , 2017, Nature Biotechnology.
[6] Benjamin E. Gross,et al. Integrative Analysis of Complex Cancer Genomics and Clinical Profiles Using the cBioPortal , 2013, Science Signaling.
[7] Bin Chen,et al. Selecting precise reference normal tissue samples for cancer research using a deep learning approach , 2019, BMC Medical Genomics.
[8] Chirag J Patel,et al. A standard database for drug repositioning , 2017, Scientific Data.
[9] Bin Chen,et al. Reversal of cancer gene expression correlates with drug efficacy and reveals therapeutic targets , 2017, Nature Communications.
[10] Avi Ma'ayan,et al. Drug Gene Budger (DGB): an application for ranking drugs to modulate a specific gene based on transcriptomic signatures , 2018, Bioinform..
[11] Peter Ertl,et al. Estimation of synthetic accessibility score of drug-like molecules based on molecular complexity and fragment contributions , 2009, J. Cheminformatics.
[12] Onur Yukselen,et al. DEBrowser: interactive differential expression analysis and visualization tool for count data , 2018, bioRxiv.
[13] J. Engelman,et al. The PI3K pathway as drug target in human cancer. , 2010, Journal of clinical oncology : official journal of the American Society of Clinical Oncology.
[14] Justin Guinney,et al. GSVA: gene set variation analysis for microarray and RNA-Seq data , 2013, BMC Bioinformatics.
[15] Philip R. O. Payne,et al. ‘RE:fine drugs’: an interactive dashboard to access drug repurposing opportunities , 2016, Database J. Biol. Databases Curation.
[16] Andrew D. Rouillard,et al. Enrichr: a comprehensive gene set enrichment analysis web server 2016 update , 2016, Nucleic Acids Res..
[17] Paul A Clemons,et al. The Connectivity Map: Using Gene-Expression Signatures to Connect Small Molecules, Genes, and Disease , 2006, Science.
[18] A. Jemal,et al. Global cancer statistics, 2012 , 2015, CA: a cancer journal for clinicians.
[19] G. Getz,et al. Inferring tumour purity and stromal and immune cell admixture from expression data , 2013, Nature Communications.
[20] Angela N. Brooks,et al. A Next Generation Connectivity Map: L1000 Platform And The First 1,000,000 Profiles , 2017 .
[21] George Papadatos,et al. The ChEMBL bioactivity database: an update , 2013, Nucleic Acids Res..
[22] Andrew H. Beck,et al. PharmacoGx: an R package for analysis of large pharmacogenomic datasets , 2015, Bioinform..
[23] Colin N. Dewey,et al. RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome , 2011, BMC Bioinformatics.
[24] Atul J. Butte,et al. In silico and in vitro drug screening identifies new therapeutic approaches for Ewing sarcoma , 2016, Oncotarget.
[25] David Haussler,et al. TumorMap: Exploring the Molecular Similarities of Cancer Samples in an Interactive Portal. , 2017, Cancer research.
[26] Emily Silgard,et al. Analysis and visualization of linked molecular and clinical cancer data by using Oncoscape , 2018, Nature Genetics.
[27] A. Butte,et al. Combined inhibition of atypical PKC and histone deacetylase 1 is cooperative in basal cell carcinoma treatment. , 2017, JCI Insight.
[28] Mark D. Robinson,et al. edgeR: a Bioconductor package for differential expression analysis of digital gene expression data , 2009, Bioinform..
[29] P. Bork,et al. Novel drug candidates for the treatment of metastatic colorectal cancer through global inverse gene-expression profiling. , 2014, Cancer research.
[30] Patrick A. Newbury,et al. Evaluating cell lines as models for metastatic cancer through integrative analysis of open genomic data , 2018, bioRxiv.
[31] A. Cabrera,et al. EWING'S SARCOMA. , 1964, Surgery, gynecology & obstetrics.
[32] Kathleen M Jagodnik,et al. Massive mining of publicly available RNA-seq data from human and mouse , 2017, Nature Communications.
[33] Jacob K. Asiedu,et al. The Drug Repurposing Hub: a next-generation drug library and information resource , 2017, Nature Medicine.
[34] Evan Bolton,et al. PubChem 2019 update: improved access to chemical data , 2018, Nucleic Acids Res..
[35] Bin Chen,et al. Leveraging Big Data to Transform Drug Discovery. , 2019, Methods in molecular biology.
[36] Yang Zhong,et al. DrugSig: A resource for computational drug repositioning utilizing gene expression signatures , 2017, PloS one.
[37] Noel Southall,et al. An integrative knowledge graph for rare diseases, derived from the Genetic and Rare Diseases Information Center (GARD) , 2020, J. Biomed. Semant..
[38] Alexander A. Morgan,et al. Discovery and Preclinical Validation of Drug Indications Using Compendia of Public Gene Expression Data , 2011, Science Translational Medicine.
[39] Robert J. Lonigro,et al. Integrative Clinical Genomics of Metastatic Cancer , 2017, Nature.
[40] S. Dudoit,et al. Normalization of RNA-seq data using factor analysis of control genes or samples , 2014, Nature Biotechnology.
[41] Jit Kang Chang,et al. DeSigN: connecting gene expression with therapeutics for drug repurposing and development , 2017, BMC Genomics.
[42] Angela N. Brooks,et al. A Next Generation Connectivity Map: L1000 Platform and the First 1,000,000 Profiles , 2017, Cell.
[43] Avi Ma'ayan,et al. Enrichr: interactive and collaborative HTML5 gene list enrichment analysis tool , 2013, BMC Bioinformatics.
[44] John J. Irwin,et al. ZINC 15 – Ligand Discovery for Everyone , 2015, J. Chem. Inf. Model..
[45] W. Huber,et al. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 , 2014, Genome Biology.
[46] Charity W. Law,et al. voom: precision weights unlock linear model analysis tools for RNA-seq read counts , 2014, Genome Biology.
[47] A. Jemal,et al. Global cancer statistics , 2011, CA: a cancer journal for clinicians.
[48] Thomas R. Gingeras,et al. STAR: ultrafast universal RNA-seq aligner , 2013, Bioinform..
[49] A. Butte,et al. Systematic pan-cancer analysis of tumour purity , 2015, Nature Communications.
[50] Chi V Dang,et al. MYC on the Path to Cancer , 2012, Cell.
[51] A. Butte,et al. Abstract 4610: A drug repositioning approach identifies tricyclic antidepressants as inhibitors of small cell lung cancer and other neuroendocrine tumors , 2014 .
[52] Brad T. Sherman,et al. The DAVID Gene Functional Classification Tool: a novel biological module-centric algorithm to functionally analyze large gene lists , 2007, Genome Biology.
[53] Marc W. Schmid,et al. Rcount: simple and flexible RNA-Seq read counting , 2015, Bioinform..